MétaCan
Menu
Back to cohort
Record W2589936655 · doi:10.4309/jgi.2017.35.3

Risk factors for pathological gambling along a continuum of severity: Individual and relational variables

2017· article· en· W2589936655 on OpenAlexvenueno aff
Diana Cunha, Bruno de Sousa, Ana Paula Relvas

Bibliographic record

VenueJournal of Gambling Issues · 2017
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyGambling disorderPathologicalOddsClinical psychologyPsychopathologyOdds ratioMarital statusHumanitiesDevelopmental psychologyPsychiatryMedicineDemographyInternal medicineLogistic regressionPopulationSociologyAddiction

Abstract

fetched live from OpenAlex

This study’s aim was to identify characteristics with higher odds of distinguishing a group of pathological gamblers (PG) from (1) a group of gamblers without a gambling problem (NP) and 2) a sub-clinical group (SP). An additional aim was to investigate those characteristics as risk/protective factors along the continuum of problem-gambling severity. Sociodemographic (gender, age, marital status, and educational level), individual (psychopathological symptoms) and relational (family functioning, dyadic adjustment, and differentiation of self) variables were considered. The sample consisted of 331 participants: 162 NP, 117 SP and 52 PG. The main results indicate that the characteristics with higher odds of distinguishing among the groups were gender, educational level, age, differentiation of self, and psychopathological symptoms. The odds of being a PG were higher for men with a low educational level and less adaptive psycho-relational functioning. Conversely, the odds of being a NP were higher for women with a high educational level and more adaptive psycho-relational functioning. Gender and educational level stood out with respect to their relevance as risk/protective factors, and their role was found to be dynamic and interdependent with the severity of problem gambling and/or the investigated psycho-relational characteristics. The risk/protective value was more remarkable when gamblers already exhibited SP.L’objectif de cette étude était d'identifier les caractéristiques présentant une probabilité plus élevée de distinguer un groupe de joueurs pathologiques (PG) d'un groupe de joueurs sans problème de jeu (NP) et un groupe sous-clinique (SP). Un autre objectif consistait à étudier ces caractéristiques en tant que facteurs de risque / protection dans le continuum de la gravité du jeu problématique. Les variables sociodémographiques (sexe, âge, état matrimonial et niveau d'instruction), individuelles (symptômes psychopathologiques) et relationnelles (fonctionnement familial, ajustement dyadique et différenciation de self) ont été prises en considération. L'échantillon comprenait 331 participants: 162 NP, 117 SP et 52 PG. Les principaux résultats indiquent que les caractéristiques ayant une plus grande probabilité de distinction entre les groupes étaient le sexe, le niveau d'instruction, l'âge, la différenciation de self et les symptômes psychopathologiques. Les probabilités d'être un PG étaient plus élevées chez les hommes ayant un faible niveau d'instruction et moins adaptative au fonctionnement psycho-relationnel. À l'inverse, les probabilités d'être NP étaient plus élevées chez les femmes ayant un niveau d'instruction élevé et un fonctionnement psycho-relationnel plus adaptatif. Le sexe et le niveau de scolarité se distinguent par leur pertinence en tant que facteurs de risque / protection et leur rôle est jugé dynamique et interdépendant de la gravité du jeu problématique et / ou des caractéristiques psycho-relationnel étudiées. La valeur risque / protection était plus remarquable lorsque les joueurs présentaient déjà SP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.342
GPT teacher head0.452
Teacher spread0.110 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Gambling IssuesSame topicGambling Behavior and TreatmentsFrench-language works237,207